钢琴音色感知响度建模:理论与应用

Yang Qu, Yutian Qin, Lecheng Chao, Hangkai Qian, Ziyu Wang, Gus G. Xia
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引用次数: 0

摘要

声音的感知响度与物理属性之间的关系是计算机音乐和心理声学中的一个重要课题。“等响度轮廓”的早期研究可以追溯到20世纪20年代,从那时起,测量的响度相对于强度和频率进行了多次修订。然而,大多数的研究仅仅集中在合成声上,对于复杂音色的自然音色的诱导理论很少得到证实。为此,本文通过对钢琴音色的建模,对自然音色响度感知的理论和应用进行了研究。理论部分包括:1)精确测量音高的钢琴音调等响度轮廓,以及2)一个机器学习模型,该模型能够纯粹基于人类受试者测量训练的光谱特征来推断响度。在应用方面,我们将我们的理论应用到钢琴控制传递中,我们在两台不同的钢琴上(在不同的声学环境下)调整MIDI速度,以达到相同的感知效果。实验表明,我们的理论响度建模和相应的性能控制传递算法都明显优于它们的基线。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling Perceptual Loudness of Piano Tone: Theory and Applications
The relationship between perceptual loudness and physical attributes of sound is an important subject in both computer music and psychoacoustics. Early studies of"equal-loudness contour"can trace back to the 1920s and the measured loudness with respect to intensity and frequency has been revised many times since then. However, most studies merely focus on synthesized sound, and the induced theories on natural tones with complex timbre have rarely been justified. To this end, we investigate both theory and applications of natural-tone loudness perception in this paper via modeling piano tone. The theory part contains: 1) an accurate measurement of piano-tone equal-loudness contour of pitches, and 2) a machine-learning model capable of inferring loudness purely based on spectral features trained on human subject measurements. As for the application, we apply our theory to piano control transfer, in which we adjust the MIDI velocities on two different player pianos (in different acoustic environments) to achieve the same perceptual effect. Experiments show that both our theoretical loudness modeling and the corresponding performance control transfer algorithm significantly outperform their baselines.
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